Design And Implementation Of Parking Space Recommendation System Based On Resource Agent

At present,the large volumes of vehicles and insufficient parking spaces in the urban areas,make it difficult for drivers to find parking places especially during peak periods of demands.Low speed vehicles in search of parking spaces easily lead to traffic congestions.The availability of parking information and the improvement of parking spaces utilization are the effective ways to solve the problem of difficult parking for drivers.The development of various technologies in the field of Internet of Things has brought about an opportunity for real-time acquisition and effective dissemination of available parking information.Many scholars have studied parking recommendation applications,which have alleviated the parking problem to some extent.However,these systems have few considerations for the heterogeneity of the representation and processing of parking space data and can’t obtain comprehensive parking information.These leads to some limitations on the guidance and recommendation for drivers.In addition,these systems are relatively simple in function,and have less consideration for personalized and intelligent parking needs of driver users.In order to solve the above problems,based on the existing technology and the analysis of parking demand for driver users,a parking space recommendation system based on resource agent is designed and implemented in this paper.The main research and work carried out in this process are as follows:Firstly,the abstract technology and standards of heterogeneous equipment and applications are studied.According to the characteristics of entities in the parking process,the concept of resource agent is introduced,and the unified resource representation model of parking application field is proposed.The actual equipment and application are abstracted into the system.The resource agent shields the heterogeneity of data so that each vehicle resource and parking lot resource(including parking space resources)can exchange data.According to the actual situation of driver parking,the active parking recommendation rule based on resource agent is proposed to dynamically determine the driver’s parking demand.According to the selection factors that affect driver parking,a parking lot recommendation strategy based on multi-attribute decision-making is proposed which can provide a personalized list of recommended parking lots for divers.Subsequently,based on driver’s needs and system functions,the software architecture of the system is designed,and the sub-function modules in the parking space recommendation system are presented.Combining the operation and service between various resource agents in the system with the parking recommendation mechanism,the main system functions such as parking space recommendation and parking space reservation are realized.Finally,the modules of the parking space recommendation system based on resource agent are implemented,and the relevant interfaces are presented and explained.The parking lot recommendation strategy is verified and proved to be effective and reasonable.